Powerful Fish in Poor Environments: Energetic Trade-Offs Drive Distribution
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Powerful fish in poor environments: Energetic trade-offs drive distribution and abundance in an extremophile forest-dwelling fish A thesis submitted in partial fulfilment of the requirements for the Degree of Master of Science in Zoology in the University of Canterbury by Richard S. A. White University of Canterbury 2013 1 Contents Abstract.....................................................................................................................................5 Chapter One: General introduction ......................................................................................... 7 Chapter Two: The abiotic-biotic stress tolerance trade-off in an extremophile forest-pool- dwelling fish: the habitat portfolio effect on distribution Abstract....................................................................................................................... 18 Introduction................................................................................................................. 19 Methods....................................................................................................................... 22 Results......................................................................................................................... 27 Discussion................................................................................................................... 33 Chapter Three: Deviations from metabolic theory of ecology drive local distribution and abundance in forest-pool-dwelling extremophile fish Abstract....................................................................................................................... 40 Introduction................................................................................................................. 41 Methods....................................................................................................................... 45 Results......................................................................................................................... 51 Discussion................................................................................................................... 56 Appendices.................................................................................................................. 63 Chapter Four: General discussion and implications for freshwater fish management ......... 64 2 Glossary ................................................................................................................................. 73 Acknowledgements ............................................................................................................... 75 References.............................................................................................................................. 77 3 Frontispiece: An adult brown mudfish ( Neochanna apoda ) swimming in an artificial aquarium with mossy vegetation and detritus typical of its forest pool habitat. Photo credit: Angus McIntosh. 4 Abstract Abstract For many species, distribution and abundance is driven by a trade-off between abiotic and biotic stress tolerance (i.e. physical stress versus competition or predation stress). This trade- off may be caused by metabolic rate differences in species such that slow metabolic rates increase abiotic tolerance but decrease biotic tolerance. I investigated how metabolic rate differences were responsible for an abiotic-biotic tolerance trade-off in brown mudfish (Neochanna apoda ) and banded kokopu ( Galaxias fasciatus ), that drives the allopatric distribution of these fish in podocarp swamp-forest pools. Brown mudfish and banded kokopu distribution across 65 forest pools in Saltwater forest, Westland National Park, New Zealand was almost completely allopatric. Mudfish were restricted to pools with extreme abiotic stress including hypoxia, acidity and droughts because of kokopu predation in benign pools. This meant the mudfish realised niche was only a small fraction of their large fundamental niche, which was the largest out of sixteen freshwater fish species surveyed in South Island West Coast habitats. Thus mudfish had a large fundamental to realised niche ratio because of strong physiological stress tolerance but poor biotic stress tolerance compared to other fish. A low metabolic capacity in mudfish compared to kokopu in terms of resting and maximum metabolic rates and aerobic scope explained the strong mudfish tolerance to extreme abiotic stress, but also their sensitivity to biotic stress by more powerful kokopu in benign pools, and hence their allopatric distribution with kokopu. Despite being restricted to extreme physical stress, mudfish populations were, in fact, more dense than those of kokopu, because of low individual mudfish resting metabolic rates, which would cause resources to be divided over more individuals. Distribution and abundance in mudfish and kokopu were therefore driven by an abiotic-biotic tolerance trade-off caused by a physiological trade-off between having slow or fast metabolic rates, respectively. The 5 Abstract negative relationship between species resting metabolic rates and their tolerance to abiotic stress provides a way of estimating the impact of human induced environmental change that can either increase or decrease habitat harshness. Thus species with low metabolic rates, like mudfish, will be negatively affected by human induced environmental change that removes abiotic habitat stress and replaces it with benign conditions. My evidence shows that extreme stressors provide a protective habitat supporting high mudfish biomass with significant conservation value that should be maintained for the long-term persistence of mudfish populations. 6 Chapter One: General Introduction Chapter One: General Introduction Introduction Understanding the drivers of distribution and abundance (D&A) is a vital theme in predictive ecology (Guisan & Thuiller 2005). Distribution and abundance can be affected by both intrinsic species traits and environmental conditions (McGill et al. 2006), both of which are highly variable, making it unlikely that general ecological laws can be applied to predict D&A at small local scales (Lawton 1999). Consequently, some ecologists have encouraged the search for ecological generalities at global macro-ecological scales, where ecological responses are averaged and local deviations are mostly considered as a nuisance residual (Lawton 1999). Although this approach has produced many generally applicable insights (Brown & Maurer 1989; Brown, Stevens & Kaufman 1996; Hawkins et al. 2003), ecological management is often applied to specific species or locations where residual variation may be more, or at least as, important as a macro-ecological prediction (Simberloff 1995). Moreover, understanding why such species or locations deviate from macro-ecological patterns may not only improve D&A predictions, and thus environmental management at local scales, but may also enrich our understanding of the fundamental laws generating the macro-ecological patterns themselves. The metabolic theory of ecology (MTE) is a macro-ecological theory that has been the focus of intense interest in recent decades (West, Brown & Enquist 1997; West, Brown & Enquist 1999; Gillooly et al. 2001; Brown et al. 2004). Metabolic theory predicts ¼ power scaling of ecological phenomena with individual or species mass because of the fundamental ¾ power scaling of resting metabolic rates (RMR) with mass (Brown et al. 2004). For example, because RMR increases with an individual’s mass with a slope of 0.75, maximum 7 Chapter One: General Introduction population density should decline with the average mass of individuals in a population with a slope of –0.75 (Damuth 1981; Brown et al. 2004). This reasoning invokes an additional fundamental concept, that maximum population carrying capacity ( C), all else being equal, should equal energy availability ( E) divided by the per-capita energy consumption rate ( Pc) (i.e. C = E / Pc) (Damuth 1981; Carbone & Pettorelli 2009). Consequently, as mass increases, 0.75 E is divided by an increasingly larger number (i.e. Pc = mass ), and therefore, C must decline (i.e. C = mass -0.75 ) (Damuth 1981; Brown et al. 2004). While this metabolic principle has had some support at large ecological scales (Damuth 1981; Nee et al. 1991), there is still large residual variation in its predictions for specific species and locations (Blackburn & Gaston 1999). Moreover, as body size range declines to that which is more likely at local scales, this residual variation increases relative to that which is explained by body size (Isaac, Storch & Carbone 2013), and the slope of the size-density relationship (SDR) can fluctuate greatly (Isaac, Storch & Carbone 2011). Consequently, the applicability of individual or species mass as a universal predictor of density may be of limited use at small scales, where location and species-specific knowledge may be more predictive. One of the most common criticisms levelled at MTE focuses on the variation in the metabolic mass scaling exponents that can exist both within and between species (Bokma 2004; Glazier 2005). Exponents can fluctuate inter-specifically from greater than 1 to nearly 0, across several taxa, and can vary greatly within species due to individual growth rate differences (Bertalanffy 1951; Glazier 2005; Czarnoł ęski et al. 2008). Only when species- specific exponents are averaged across taxa does the exponent approach 0.75, and consequently, the universal